The interplay of product and process in skunkworks identity work: An inductive model
Bibliographic record
Abstract
Research Summary The success of skunkworks often involves nurturing an identity at odds with the parent firm, which may cause de‐identification with the firm and hamper reintegration of team members post‐project. This identity work could lead to market success but organizational failure as skunkworks' members distance themselves from the parent firm tasking the innovation. To explore the when and how of identity work throughout a skunkworks' lifecycle, we studied a skunkworks at an international consumer products company over a 35‐month research window and through post‐hoc interviews some 15 years later. Using a grounded theory approach, we documented the interplay between product (needs) and process (decisions) over the skunkworks' lifecycle, and constructed an inductive model providing important insight to the micro‐foundations of the identity‐based view of competitive advantage. Managerial Summary This study examines how identity work unfolds over time in a skunkworks team created to spur breakthrough innovation. Such teams can develop a strong sense of identity that may in part involve opposition to the parent firm. While this can motivate the team to galvanize around the task at hand, such “othering” may cause de‐identification with the parent and hamper reintegration of team members after the skunkworks is dissolved. Thus, identity work within a skunkworks can lead to both market success and organizational failure. We ground our model in a 35‐month study of an international consumer products company, documenting the interplay between product (needs) and process (decisions) over the skunkworks' lifecycle. We provide prescriptions as to how to mitigate the possibility of these negative outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".